AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin

Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate

Dexterity for Channel Capacity Enhancement in MU-MIMO by Abrogating Interference

The looming field of Multi user Multiple-input Multiple-output (MU-MIMO) communication system has faced a challenge with precoding techniques for achieving increased channel capacity of their less inhaling of signals, imperfect knowing of channel state information, loss of signals by noise ,time complexity etc. in downlink systems which results in interference to the users. Hence straight forwarding from the issues, the paper newly introduce2LB-FR precoding technique which holds Linde-Lyold’s (LL)algorithm to increase data transmission by consuming large amount of signals with space and the Bernoulli distribution with Bayes decision (BB) to allot the perfect channel state; l information during transmission that eliminates co-interference. Holding Floyd Rasta (FR) algorithm expels the noise if added and takes the shortest required path by acquiring all the possible routes available in single execution which decreases delay. By the overall implementation, the proposed work pomped that in short time ,the capacity of the channel get enhanced with interference cancellation

Sum Rate and Fairness Analysis for the MU-MIMO Downlink under PSK Signalling: Interference Suppression vs Exploitation

In this paper, we analyze the sum rate performance of multi-user multiple-input multiple-output (MU-MIMO) systems, with a finite constellation phase-shift keying (PSK) input alphabet. We analytically calculate and compare the achievable sum rate in three downlink transmission scenarios: 1) without precoding, 2) with zero forcing (ZF) precoding 3) with closed form constructive interference (CI) precoding technique. In light of this, new analytical expressions for the average sum rate are derived in the three cases, and Monte Carlo simulations are provided throughout to validate the analysis. Furthermore, based on the derived expressions, a power allocation scheme that can ensure fairness among the users is also proposed. The results in this work demonstrate that, the CI strictly outperforms the other two schemes, and the performance gap between the considered schemes increases with increase in the MIMO size. In addition, the CI provides higher fairness and the power allocation algorithm proposed in this paper can achieve maximum fairness index

Multiplexing, scheduling, and multicasting strategies for antenna arrays in wireless networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (p. 167-174).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.A transmitter antenna array has the ability to direct data simultaneously to multiple receivers within a wireless network, creating potential for a more integrated view of algorithmic system components. In this thesis, such a perspective informs the design of two system tasks: the scheduling of packets from a number of data streams into groups; and the subsequent spatial multiplexing and encoding of these groups using array processing. We demonstrate how good system designs can help these two tasks reinforce one another, or alternatively enable tradeoffs in complexity between the two. Moreover, scheduling and array processing each benefit from a further awareness of both the fading channel state and certain properties of the data, providing information about key flexibilities, constraints and goals. Our development focuses on techniques that lead to high performance even with very low-complexity receivers. We first consider spatial precoding under simple scheduling and propose several extensions for implementation, such as a unified time-domain precoder that compensates for both cross-channel and intersymbol interfer- ence. We then show how more sophisticated, channel-aware scheduling can reduce the complexity requirements of the array processing. The scheduling algorithms presented are based on the receivers' fading channel realizations and the delay tolerances of the data streams. Finally, we address the multicasting of common data streams in terms of opportunities for reduced redundancy as well as the conflicting objectives inherent in sending to multiple receivers. Our channel-aware extensions of space-time codes for multicasting gain several dB over traditional versions that do not incorporate channel knowledge.by Michael J. Lopez.Ph.D

Multiplexing, Scheduling, and Multicasting Strategies for Antenna Arrays in Wireless Networks

Grant number: CCR-9979363A transmitter antenna array has the ability to direct data simultaneously to multiple receivers within a wireless network, creating potential for a more integrated view of algorithmic system components. In this thesis, such a perspective informs the design of two system tasks: the scheduling of packets from a number of data streams into groups; and the subsequent spatial multiplexing and encoding of these groups using array processing. We demonstrate how good system designs can help these two tasks reinforce one another, or alternatively enable tradeoffs in complexity between the two. Moreover, scheduling and array processing each benefit from a further awareness of both the fading channel state and certain properties of the data, providing information about key flexibilities, constraints and goals. Our development focuses on techniques that lead to high performance even with very low-complexity receivers. We first consider spatial precoding under simple scheduling and propose several extensions for implementation, such as a unified timedomain precoder that compensates for both cross-channel and intersymbol interference. We then show how more sophisticated, channel-aware scheduling can reduce the complexity requirements of the array processing. The scheduling algorithms presented are based on the receivers’ fading channel realizations and the delay tolerances of the data streams. Finally, we address the multicasting of common data streams in terms of opportunities for reduced redundancy as well as the conflicting objectives inherent in sending to multiple receivers. Our channel-aware extensions of space-time codes for multicasting gain several dB over traditional versions that do not incorporate channel knowledge.NSF, HP/MIT Alliance